Here we introduce the LASP code, which is designed for large‐scale atomistic simulation of complex materials with neural network (NN) potential. The software architecture and functionalities of LASP will be overviewed. LASP features with the global neural network (G‐NN) potential that is generated by learning the first principles dataset of global PES from stochastic surface walking (SSW) global optimization. The combination of the SSW method with global NN potential facilitates greatly the PES exploration for a wide range of complex materials. Not limited to SSW‐NN global optimization, the software implements standard interfaces to dock with other energy/force evaluation packages and can also perform common tasks for computing PES properties, such as single‐ended and double‐ended transition state search, the molecular dynamics simulation with and without restraints. A few examples are given to illustrate the efficiency and capabilities of LASP code. Our ongoing efforts for code developing and G‐NN potential library building are also presented.
This article is categorized under:
Software > Simulation Methods
Here, by combining machine learning with the latest stochastic surface walking (SSW) global optimization, we explore for the first time the potential energy surface of β-B.
Glucose pyrolysis, a model system in biomass utilization,
is renowned
for its great complexity, deep in reaction network hierarchy and rich
in reaction patterns. The selectivity in glucose pyrolysis, e.g.,
the high yield of 5-hydroxymethylfurfural (HMF), a value-added platform
product, remains an intriguing puzzle even after 60 years of experimental
study. Here we resolve the whole reaction network of glucose pyrolysis
using a global-to-global technique for reaction pathway sampling.
This is achieved by establishing the first organic chemistry reaction
database via stochastic surface walking (SSW) global optimization,
building the global neural network (G-NN) potential via machine learning
and extensively exploring the reaction network of glucose pyrolysis.
In total, 6407 elementary reactions, screened out from more than 150 000
reaction pairs in glucose pyrolysis, are collected in our reaction
database. The established reaction network from SSW-NN, further validated
by first-principles calculations, reveals that for glucose to HMF,
the lowest energy reaction pathway involves fructose and 3-deoxyglucos-2-ene
(3-DGE) as key intermediates and a site-selective reaction type, retro-Michael-addition,
for three consecutive dehydration steps. The overall barrier is determined
to be 1.91 eV, being at least 0.19 eV lower than all previously proposed
mechanisms, which assumes direct β-H elimination dehydration.
The lowest pathways to the other two major products, furfural (FF)
and hydroxyacetaldehyde (HAA), are also discovered with a similar
barrier 1.95 eV, which exhibit a competing nature by sharing the same
key intermediate, 3-ketohexose. Since chemical reactions occurring
in fast glucose pyrolysis are generally present in biomass chemistry,
containing essentially all reaction patterns of C–H–O
elements, the methodology designed and the results presented would
help to advance reaction design and mechanistic modeling in renewable
fuels from biomass.
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